Dietary patterns derived by Gaussian graphical models and metabolic profiles among overweight and obese individuals.

ABSTRACT:

Background

The increasing prevalence of metabolic syndrome (MetS) and its associated risk factors highlights the critical need to understand dietary patterns that influence health outcomes, particularly among overweight and obese individuals. Identifying dietary networks provides valuable insights into the complex interactions between food groups within typical dietary patterns. This study aimed to derive dietary networks using Gaussian graphical models (GGM) and evaluate their associations with the risk of MetS components in a sample of the Iranian population.

Methods

This cross-sectional study involved 647 participants who were overweight or obese. The study included assessments of body composition and anthropometric measurements. Dietary fatty acid consumption was evaluat

SUBMITTER: Hemami RM 

PROVIDER: S-EPMC11971342 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature